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Behavior-based price discrimination and customer information sharing

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  • De Nijs, Romain

Abstract

This article investigates the incentives and effects of rival firms sharing their customers’ identities, using a two-period model with behavior-based price discrimination (BBPD). A unilateral information exchange between the two periods takes place in a subgame-perfect equilibrium. This exchange increases the ability of the firms to discriminate prices amongst consumers according to their profiles, and boosts the profitability of BBPD at the customers’ expense.

Suggested Citation

  • De Nijs, Romain, 2017. "Behavior-based price discrimination and customer information sharing," International Journal of Industrial Organization, Elsevier, vol. 50(C), pages 319-334.
    • Handle: RePEc:eee:indorg:v:50:y:2017:i:c:p:319-334
    DOI: 10.1016/j.ijindorg.2016.12.003
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Chen, Chen & Duan, Yongrui, 2022. "Impact of personalization and privacy concerns on information disclosure and pricing," Journal of Retailing and Consumer Services, Elsevier, vol. 69(C).
    2. repec:dpr:wpaper:1083r is not listed on IDEAS
    3. Umezawa, Masashi, 2022. "Behavior-based price discrimination in a horizontally and vertically differentiated duopoly with switching costs," Information Economics and Policy, Elsevier, vol. 61(C).
    4. Chioveanu, Ioana, 2024. "Consumer data and price discrimination by consideration sets," Economics Letters, Elsevier, vol. 236(C).
    5. Shrivastav, Sumit, 2023. "Information, mis-information, and history-based price discrimination in a duopoly," Information Economics and Policy, Elsevier, vol. 65(C).
    6. Sumit Shrivastav, 2021. "Price discrimination with imperfect consumer recognition," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2021-017, Indira Gandhi Institute of Development Research, Mumbai, India.
    7. Yongrui Duan & Yuncong Xie & Yihong Hu, 2023. "The value of personal information in vertically differentiated markets with privacy concerns," Annals of Operations Research, Springer, vol. 329(1), pages 425-469, October.
    8. Ronen Gradwohl & Moshe Tennenholtz, 2022. "Pareto-Improving Data-Sharing," Papers 2205.11295, arXiv.org.
    9. Michel Tolksdorf, 2023. "On Point Predictions and Reference Dependence in Behavior-Based Pricing Experiments," Journal of Economics and Behavioral Studies, AMH International, vol. 15(1), pages 1-14.
    10. Chongwoo Choe & Noriaki Matsushima & Mark J. Tremblay, 2020. "Behavior-Based Personalized Pricing: When Firms Can Share Customer Information," ISER Discussion Paper 1083, Institute of Social and Economic Research, Osaka University.
    11. Jean-Pierre I. Rest & Alan M. Sears & Li Miao & Lorna Wang, 2020. "A note on the future of personalized pricing: cause for concern," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(2), pages 113-118, April.
    12. Capponi, Giovanna & Corrocher, Nicoletta & Zirulia, Lorenzo, 2021. "Personalized pricing for customer retention: Theory and evidence from mobile communication," Telecommunications Policy, Elsevier, vol. 45(1).
    13. Jihwan Do, 2023. "Joint market dominance through exclusionary compatibility," International Journal of Game Theory, Springer;Game Theory Society, vol. 52(4), pages 1077-1110, December.
    14. Choe, Chongwoo & Matsushima, Noriaki & Tremblay, Mark J., 2022. "Behavior-based personalized pricing: When firms can share customer information," International Journal of Industrial Organization, Elsevier, vol. 82(C).

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